The multi-user MIMO system is a closed loop MIMO solution, in which the base station schedules in accordance with channel information fed back from each mobile station to enable a plurality of users to simultaneously transmit data on a plurality of antennas within the same time and frequency resource, with each user occupying one or more data streams. Since signals of a plurality of users are transmitted simultaneously within the same time and frequency resource, it is necessary for the scheduled user to separate the data streams of his own. Separation of data streams can be done at the user terminal or pre-separated at the base station terminal. The former method is referred to as unitary pre-coding, while the latter method is called zero-forcing pre-coding. This paper mainly concentrates on the multi-user MIMO solution employing zero-forcing pre-coding, whose typical structure is shown in FIG. 1. The processing procedure is as follows:    1) User terminal UE (such as UE 1 . . . UE n) performs channel estimation to obtain a channel matrix H, whose reception vector v1 is calculated to obtain an effective channel vector heff, represented as: heff=v1H. Singular value decomposition is performed thereon to obtain H=UΣTH, where U and T are unitary matrixes and Σ is a diagonal matrix. The reception vector v1=u1H, namely the conjugate transpose of the first column vector of the matrix U.    2) The base station and the user terminal hold the same codebook; suppose a vector set contained in the codebook be S={s1, s2, . . . , sN}, the effective channel vector heff is quantized by using the vectors in the codebook to obtain h=si,
      i    =          arg      ⁢                          ⁢                        max                      1            ≤            j            ≤            N                          ⁢                                        〈                                          h                eff                            ,                              s                j                                      〉                                          ,where h is the quantized channel vector, and where eff, sj denotes the inner product between vectors heff and sj.    3) Calculate CQI value, and feed back CQI and index i of the quantized vector si as selected to BS.    4) BS terminal scheduler (base station scheduler) determines a user group in accordance with a scheduling algorithm, and a matrix C is constructed in accordance with vector indexes fed back from each user of the user group. A transformation matrix with the pre-coding matrix as the matrix C is represented as: G=C(CCH)−1.
Due to the quantization of the effective channel and other factors such as feedback delay, the zero-forcing pre-coding solution cannot achieve perfect separation of data streams transmitted from each scheduled user. If the base station terminal transmits a zero-forcing pre-coding matrix to each scheduled user, it will be possible for the user terminal to perform mean square error estimation MMSE by using the pre-coding matrix known in advance to further reduce interference between multiple users (refer for this method to 3GPP R1-070346, Philips, “Comparison of MU-MIMO feedback schemes with multiple UE receive antennas”). Since wireless frequency spectrum is very costly, the base station has to reduce the downlink signaling overhead to save bandwidth occupied by the downlink as much as possible while notifying the user of the pre-coding matrix used.
Two existent methods for transmitting the pre-coding matrix are described below. Taking an example where the base station terminal uses 4 emission antennas, the maximum number of users capable of being scheduled is four, namely, the number of users capable of being simultaneously scheduled can be two, three or four. Accordingly, in order to search a user combination having the maximum data rate, the optimal number of user combinations selected is in principle:
      N    =                            ∑                      i            =            2                    4                ⁢                  (                                                    K                                                                    i                                              )                    =                        C          K          2                +                  C          K          3                +                  C          K          4                      ,where K indicates the number of vectors in the codebook. Taking for example a 4-bits Grassmannian codebook that contains 16 vectors, the signaling overhead required for the base station to notify the scheduled user are log2 N=┌log2 2500┐=12 bits. As can be seen, such user selection solution requires too large a number of user groups to be selected as well as requires high complexity. Another method can be referred to in the method proposed in 3GPP R1-072514, Freescale Semiconductor Inc, “Codebook Design for MU-MIMO”. Taking also for example the 4-bits Grassmannian codebook, if four users are simultaneously scheduled, the signaling overhead should firstly include the number of simultaneously scheduled users, which requires 2 bits, and should then notify the index of each vector in the pre-coding matrix, which requires 4 bits for each vector, so that it requires 16 bits to transmit the pre-coding matrix. That is to say, the downlink requires 18 bits altogether. In addition, since it is necessary for downlink control signaling to employ low coding rate and low modulation mode, the total signaling overhead of the aforementioned two methods requires relatively more data symbols.